Commercially available sunflower oil was enriched in polyphenols by adding olive leaf extract. After extracting the dried and ground olive leaves with the assistance of homogenizer, total phenolic content (TPC) and oleuropein concentration of the extract were determined. The dried extract was partially dissolved into the sunflower oil to increase the quality and shelf-life of the oil enriched by the substances in the plants by means of solid-liquid extraction method. A face central composite design (FCCD) through response surface methodology (RSM) was used to investigate the effects of enrichment conditions (extract content, time and mixing speed) on the responses, TPC and oleuropein concentration of the enriched sunflower oil as well as to design of experiments, to model and to optimize the process. The enriched sunflower oil obtained at optimum conditions was evaluated in terms of its TPC, oleuropein, total carotenoid content (TCC), antioxidant activity (AA), peroxide value (PV) and induction time (IT), depending on those of the crude oil. Furthermore, artificial neural networks (ANN) were also employed to compare the predicted results of RSM.